Each year, more than 25,000 cases of invasive cancer attributable to human papillomavirus (HPV) infection occur in the United States; nearly 50% are cervical cancer, while the rest involve the oral cavity/oropharynx, anus, vulva, penis, and vagina. Collectively, these account for substantial morbidity and mortality, contribute to health disparities, and are associated with high economic costs. Advancements in HPV-related cancer epidemiology, coupled with new (e.g., HPV-16,-18 vaccines, HPV DNA testing) and emerging (e.g., biomarkers, therapeutic vaccines) technologies provide a remarkable opportunity to improve cancer prevention efforts. However, critical challenges remain with respect to clinical decision-making and prevention policy, pertaining to knowledge gaps and heterogeneities in the natural history of different cancers, uncertainties in HPV type distribution following HPV-16,-18 vaccination, and the real-world clinical effectiveness of emerging technologies. We propose to employ a decision-analytic approach, developing a flexible modeling framework that will allow us to synthesize the best available data; evaluate the health and economic consequences of alternative strategies; explore the uncertainty around their outcomes; explicitly quantify the tradeoffs associated with different approaches; and inform timely clinical and policy questions. By achieving our aims, we expect to have an impact on (1) the analytic methods of decision science; (2) the equitable distribution and rationale use of new technology; (3) the effectiveness of strategies for cancer prevention through clinical guidelines and national policies; (4) HPV-related cancer outcomes, including reduced incidence, enhanced quality of life, improved survival, and reduced disparities; and (5) the financial and economic profile of delivering cancer-related health services.